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In this research, multivariate statistical analysis was performed on twenty water quality parameters (WQP) collected on tri-monthly basis (four times/year) from 441 drinking water sources in Newfoundland and Labrador (NL), Canada for 18 years (1999-2016). The WQP included alkalinity (Alk), color (Col), conductivity (Cond), hardness (Hard), pH, total dissolved solids (TDS), turbidity (Turb), bromide (Br), calcium (Ca), chloride (Cl), fluoride (F), potassium (K), sodium (Na), sulfate (SO 4 ), dissolved organic carbon (DOC), ammonia (NH 3 ), nitrate (NO 3 ), Kjeldahl nitrogen (N), total phosphorus (P) and magnesium (Mg). The assessment was conducted on surface water (SWS) and groundwater (GWS) sources separately. In SWS and GWS, number of samples analyzed for each WQP were in the ranges of 3434-6057 and 1915-1919 respectively. Averages of DOC and pH showed increasing trends (SWS: DOC = 0.0722 mg/L/year; pH = 0.0375 units/year; GWS: DOC = 0.0491 mg/L/year; pH = 0.0441 units/year) while the other WQP showed variable characteristics, which could increase treatment cost and deteriorate tap water quality. Strong correlations were observed for Ca-Hard (r = 0.97-0.98), TDS-Cond (r = 0.91-0.99) and Na-Cl (r = 0.87-0.96). In SWS, Alk had stronger correlations with Cond, Hard, pH, TDS, Ca and Mg (r = 0.62-0.94) than GWS (r = 0.56-0.63). Principal Component Analysis revealed separate clusters for DOC-Col, Na-Cl, TDS-Cond, Ca-Alk and Mg-Hard, indicating that these WQP moved together. In SWS and GWS, six principal components were significant (eigenvalue ≥ 1.0), and explained 74.8% and 72.9% of overall variances respectively. In Factor Analysis, six varifactors explained 73.4% and 70.5% of total variances in SWS and GWS respectively. For SWS and GWS, eleven and ten WQP, respectively explained these variances, indicating 45% and 50% data reduction respectively. The findings can assist in controlling water quality through monitoring reduced number of WQP, which is likely to minimize the monitoring cost., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

The fly ash from the Corner Brook Pulp and Paper (CBPP) mill was used in this study as the raw material for the preparation of a low-cost adsorbent for arsenic removal from the well water of Bell Island. The CBPP fly ash was physically activated in two different ways: (a) activation with pure CO 2 (CAC) with the iodine number and methylene value of 704.53 mg/g and 292.32 mg/g, respectively; and (b) activation with a mixture of CO 2 and steam (CSAC) with the iodine number and methylene value of 1119.98 mg/g and 358.95 mg/g, respectively, at the optimized temperature of 850 °C and the time of 2 h for both activations. The BET surface areas of the CAC and CSAC at the optimized conditions were 847.26 m 2 /g and 1146.25 m 2 /g, respectively. The optimized CSAC was used for impregnation with iron (III) chloride (FeCl 3 ) with different concentrations (0.01 M to 1 M). The study shows that the adsorbent impregnated with 0.1 M FeCl 3 is the most efficient adsorbent for arsenic removal. Isotherm analysis shows that the Langmuir model better describes the equilibrium behavior of the arsenic adsorption from both local well water and synthesized water compared to the other models. The maximum arsenic adsorption capacity was 35.6 μg/g of carbon for local well water and 1428.6 μg/g of carbon for synthesized water. Furthermore, the kinetic behavior of arsenic adsorption from synthesized and local well water was well depicted by the pseudo-second order kinetic model., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Heavy metals in drinking water pose a threat to human health. Populations are exposed to heavy metals primarily through water consumption, but few heavy metals can bioaccumulate in the human body (e.g., in lipids and the gastrointestinal system) and may induce cancer and other risks. To date, few thousand publications have reported various aspects of heavy metals in drinking water, including the types and quantities of metals in drinking water, their sources, factors affecting their concentrations at exposure points, human exposure, potential risks, and their removal from drinking water. Many developing countries are faced with the challenge of reducing human exposure to heavy metals, mainly due to their limited economic capacities to use advanced technologies for heavy metal removal. This paper aims to review the state of research on heavy metals in drinking water in developing countries; understand their types and variability, sources, exposure, possible health effects, and removal; and analyze the factors contributing to heavy metals in drinking water. This study identifies the current challenges in developing countries, and future research needs to reduce the levels of heavy metals in drinking water., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Environmental risk management strategy often encounters conflicting criteria of a subjective and objective nature that are associated with a particular management system concerning multicriteria decision making. In this study, a combination of subjective and objective criteria for risk management has been applied for drinking water treatment technology. Fuzzy set theory has been incorporated in this study. Fuzzy triangular membership functions have been developed to capture uncertainties of the model parameter values. The analytic hierarchy process has been incorporated to construct subjective priority schemes for different hierarchy level attributes. In developing subjective priority schemes, flexible ranges of importance were considered; thus the uncertainties associated with crisp values were incorporated. Using the concept of entropy, subjective importance of the objective attributes have been transformed into integrated importance. The overall ranking was evaluated based on subjective and objective criteria. An example of human health risk management from drinking water disinfection by-products has been presented through several drinking water treatment technologies. Finally, the best treatment technology is outlined. [ABSTRACT FROM AUTHOR]

Chlorine is the most commonly used disinfectant for water treatment but when in contact with organic precursors it produces toxic compounds known as trihalomethanes (THMs). Chloroform is the most commonly occurring THM and constitutes approximately 90% of the THM concentration. A study was conducted in Newfoundland for estimating the chloroform content in the drinking water supplies in Clarenville and St. John's. The sampling program was conducted in two stages, July and October-November. Higher concentrations of chloroform were observed in Clarenville but in St. John's the concentrations were within Health Canada guidelines. The chloroform is a probable human carcinogen and is categorised as `B2' by U.S. Environmental Protection Agency (U.S. EPA). The human health risk associated with consumption of drinking water was estimated by performing probabilistic analysis. In the first phase bootstrap simulations (B = 250) were performed to calculate the variability in the data. The normal distribution was found the best-fitted distribution to chloroform concentration data. For each bootstrapped run 1000 Monte Carlo Simulations (MCS) were performed in the second phase. The cancer risk was estimated using dose-response relationship of chloroform. Appropriate probability density functions (PDFs) were defined subjectively for intake rate, body weight, exposure duration, exposure frequency and averaging time. The excess lifetime human cancer risk varied from 0.5 × 10-4 to 4.0 × 10-4, and zero to 1.0 × 10-4 for Clarenville and St. John's, respectively. The average cancer risks in Clarenville and St. John's communities were 1.2 × 10-4 and 2.5 × 10-5. The estimated probabilities of exceedences above 100 ppb (μg L-1), were 100 and 2.5% for Clarenville and St. John's, respectively which emphasised the need for water treatment. Granular Activated Carbon (GAC) was proposed as one of the potential treatment technology for risk reduction in St. John's community. The treatment efficiency of a proposed technology was assumed uniformly distributed and revised risks were calculated. The average risk in St. John's can be reduced to 8.0 × 10-6 after treatment. [ABSTRACT FROM AUTHOR]